It relates to noise level estimation techniques applied to digital video signals. These techniques for estimating noise level are used in noise reduction techniques. Noise reduction techniques are generally applied to digital video images taking the form of a matrix of samples; each sample is composed of a luminance signal and, for a colour signal, of a chrominance signal.
The acquisiton of video image sequences is today still widely carried out in analogue form so that the images, once acquired and possibly forwarded and stored in analogue formats, exhibit an appreciable share of noise in their content. Once digitized, these images are also often subjected to storage/editing operations which, in their turn, introduce noise of a digital nature, this time. Finally, an image sequence generally undergoes a succession of transformations resulting in spatio-temporal noise of a strongly random nature.
To obtain high-performance functioning, noise reduction methods calling upon recursive filtering consider the very strong temporal correlation of the images of a video sequence. Consequently, the concepts of motion and of displacement are important in the fine-tuning of effective noise reduction.
The term <<displacement>> is understood to mean the change in position of an object in a scene, this change in position being localized and specific to this object. The term <<motion>> is understood to mean the entire set of displacements of objects in a video sequence.
Motion is conventionally detected either by simple image-to-image differencing, or by using a motion estimator.
When a motion estimator is used, the displacements are taken into account by computing image differences at distinct instants as well as by moving spatially within the frames. These displacements are represented by motion vector fields applied to pixels (pixelwise motion estimation) or to blocks (blockwise motion estimation). Motion-compensated image differences, called DFDs (Displacement Frame Differences), are thus obtained pixelwise or blockwise.
In known systems, the estimation of the noise level is done at the level of the image frames. This estimation leads to the noise being made uniform over the frame, and consequently the filtering also, this possibly giving rise to certain defects such as loss of definition over certain noise-free zones, the appearance of blur or the smoothing of certain textures (lawns for example). Such systems are for example described in French Patent Application 009684 filed on 24 Jul. 2000 in the name of the Thomson Multimédia Company.